code: def test_eg_conv_with_sparse_input_feature():
      x = torch.randn(4, 16).to_sparse_coo()
      edge_index = torch.tensor(
          [[0, 0, 0, 1, 2, 3], [1, 2, 3, 0, 0, 0]]
      )
  
      conv = EGConv(16, 32)
      assert conv(x, edge_index).size() == (4, 32)
  
file_path: pytorch_geometric/test/nn/conv/test_eg_conv.py
imports: import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.nn import EGConv
  from torch_geometric.testing import is_full_test
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import to_torch_csc_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: test_eg_conv_with_sparse_input_feature() without return types